In modern drug discovery, the journey from an initial hit to a promising lead series is an iterative multidisciplinary process. Combining innovative computational chemistry tools and methods with traditional medicinal chemistry, biological evaluation, and DMPK allows for greater insights and better decision making. Understanding how to navigate hit to lead is crucial for accelerating project timelines while balancing risk, cost, and efficiency.

Identifying hits that display biological activity against the primary target of interest, for example through screening (including virtual screening), fragment growing, or scaffold hopping is a key initial step, offering an opportunity to progress a validated compound series, through the hit to lead phase, for further development in the lead optimization phase. In addition to increasing the biological activity, other parameters that need to be considered include, selectivity over undesired off-targets, and control of physical chemistry properties such as logP, TPSA, along with the number of hydrogen bond donors and acceptors in the compound, to mitigate aspects like solubility, cell permeability, and metabolic stability.

Computational free energy calculation methods provide opportunities to rationalize and prioritize design ideas, with accurate predictions allowing profiling of ligands in silico prior to embarking on an expensive synthesis campaign. Approaches such as MM/GBSA offer a quick and cost effective estimate of binding energy, while Free Energy Perturbation (FEP) provides more rigorous predictions of both relative (ligands within a congeneric series) and absolute (independent of structural similarity between ligands) free energies.